Deep dives into system design, architecture patterns, and building software at scale.
A complete comparison of rate limiting algorithms — fixed window, sliding window log, sliding window counter, token bucket, leaky bucket — with trade-offs, comparison tables, distributed implementations, and Redis Lua scripts.
Master async processing patterns — fire-and-forget, request-reply, pub/sub, work queues, delayed processing, batch jobs, long-running tasks, polling vs webhooks, and tools like Celery, Bull, and Temporal.
Deep dive into consistent hashing — ring-based hashing, virtual nodes, rebalancing, jump consistent hashing, rendezvous hashing, and real-world applications in Cassandra, DynamoDB, CDNs, and load balancers.
A practical guide to CQRS — command vs query separation, separate read/write models, event sourcing integration, eventual consistency trade-offs, and when CQRS is overkill.
Understand data consistency patterns — strong vs eventual consistency, read-your-writes, causal consistency, bounded staleness, linearizability, and Jepsen testing for distributed systems.
Horizontal vs vertical partitioning, sharding strategies (hash, range, directory, geo), shard key selection, cross-shard queries, rebalancing, hot spots, and tools like Vitess and Citus.
How distributed systems resolve data conflicts — last-writer-wins, merge functions, CRDTs, version vectors, application-level resolution, and designing conflict-free architectures.
Why every microservice needs its own database — data ownership, consistency challenges, saga pattern, API composition, event-driven sync, CQRS, and polyglot persistence explained.
A comprehensive guide to dead letter queue patterns — why DLQs matter, retry exhaustion strategies, DLQ consumers, alerting on queue depth, replay strategies, poison message handling, and tools like SQS DLQ, Kafka DLT, and RabbitMQ DLX.
A comprehensive guide to distributed configuration management: architecture patterns, comparing Consul KV, etcd, and Spring Cloud Config, implementing hot reload, configuration versioning, and treating feature flags as configuration.
How to run millions of scheduled jobs across a cluster — cron at scale, job deduplication, at-least-once vs exactly-once semantics, priorities, work stealing, and tools like Temporal, Airflow, Quartz, and Hangfire.
Compare Raft, Paxos, PBFT, and Zab consensus algorithms — performance, complexity, fault tolerance, use cases, and implementation difficulty for distributed systems.
Byzantine failures, crash failures, network partitions, clock skew, split brain, cascading failures, gray failures, and detection strategies including heartbeats and phi accrual failure detectors.
A comprehensive guide to the fan-out fan-in pattern — scatter-gather, parallel processing, aggregation, map-reduce, fork-join, fan-out on write vs read, queue-based fan-out, and tools like SQS, Lambda, and Step Functions.
A comprehensive guide to leader election in distributed systems — Bully algorithm, Ring algorithm, Raft leader election, ZooKeeper ephemeral nodes, lease-based election, split-brain prevention, fencing tokens, and Kubernetes leader election.
Master microservices communication patterns — REST, gRPC, message queues, event-driven architecture, sagas, service mesh, and resilience patterns like retry, timeout, and circuit breaker.
A comprehensive guide to migrating from a monolith to microservices — domain decomposition, strangler fig pattern, database splitting, shared library extraction, team restructuring, and measuring migration success.
Master queue-based architecture — work queues vs pub/sub, priority queues, delay queues, FIFO guarantees, visibility timeout, poison pill handling, and tools like SQS, Celery, and Bull.
Client-side vs server-side discovery, service registries (Consul, etcd, ZooKeeper, Eureka), DNS-based discovery, health checking, service mesh, and Kubernetes DNS patterns.
A comprehensive reference of all 250 system design articles organized by category — fundamentals, distributed systems, architecture patterns, interview prep, infrastructure, security, data engineering, and AI/ML.
The ultimate capstone — 300 articles of system design organized by category, learning paths, key takeaways, and a roadmap for mastering distributed systems.
A concise system design cheat sheet — key numbers, common components, step-by-step framework, design patterns, scaling checklist, and monitoring essentials for interviews and real-world architecture.
Master system design tradeoffs — consistency vs availability, SQL vs NoSQL, monolith vs microservices, sync vs async, latency vs throughput, and how to discuss tradeoffs in interviews.
A deep dive into workflow engine architecture — durable execution, Temporal and Cadence, workflow as code, activity retries, timers, signals, queries, versioning, and real-world use cases.
Deep dive into the two-phase commit protocol (2PC) — prepare/commit phases, coordinator/participant roles, the blocking problem, 3PC improvement, XA transactions, and when to choose 2PC vs saga patterns.
Prevent system overload with backpressure — load shedding, rate limiting, queue depth monitoring, and reactive streams. Patterns from Kafka, gRPC, and TCP with architecture examples.
A practical guide to blockchain architecture covering consensus mechanisms (PoW, PoS, PBFT, DPoS), smart contracts, Layer 1 vs Layer 2 scaling, rollups, state channels, and when blockchain is the right choice over a traditional database.
Design a calendar system like Google Calendar — event CRUD, recurring events (RFC 5545), time zone handling, availability, scheduling conflicts, invitations, reminders, CalDAV sync, and shared calendars.
A comprehensive guide to chat system architecture covering WebSocket connections, message storage, read receipts, typing indicators, group chats, media attachments, push notifications, message ordering, presence, end-to-end encryption, and scaling strategies.
Implement the circuit breaker pattern and related resilience strategies — bulkhead, retry with backoff, timeout, fallback — using Resilience4j, Polly, and Hystrix. Plus chaos engineering basics.
A deep dive into distributed consensus algorithms — Raft consensus, Paxos algorithm, PBFT, and Zab — covering CAP theorem trade-offs, leader election, quorum-based replication, and real-world usage in CockroachDB, TiKV, and etcd.
The essential concepts behind every large-scale system — CAP theorem, consistency models, consensus algorithms, distributed transactions, failure modes, and how to design for reliability.
A deep dive into file sharing system design — covering Dropbox/Google Drive-style sync, chunking, deduplication, delta sync, metadata services, block storage, conflict resolution, permissions, real-time collaboration, versioning, and offline support.
Design geographically distributed systems with multi-region replication, consistency trade-offs, geo-routing, active-active architectures, conflict resolution, and GDPR-compliant data residency.
Make your APIs safe to retry — idempotency keys, database constraints, deduplication patterns, and real-world examples from Stripe, AWS, and Kafka.
A comprehensive guide to load balancing algorithms including round robin, weighted round robin, least connections, IP hash, and consistent hashing. Compare Nginx, HAProxy, AWS ALB/NLB, Envoy, and Traefik with configuration examples.
A comprehensive guide to push notification system design — covering requirements, notification types, delivery pipelines, prioritization, user preferences, device token management, FCM/APNs, template engines, analytics, and throttling at scale.
Design a distributed rate limiter — token bucket, sliding window log, sliding window counter, Redis-based distributed limiting, race conditions, rate limit headers, and client-side handling.
Deep dive into API rate limiting strategies — fixed window, sliding window, token bucket, leaky bucket — with Redis implementations, distributed patterns, and client-side handling.
A comprehensive system design guide covering the most important concepts, learning paths, interview strategies, and a curated index of 200 articles — the definitive resource for engineers.
A comprehensive system design roadmap covering every topic from APIs and databases to ML systems and security. Your complete guide to learning system design, organized into 5 progressive stages.
How to design a unique ID generator for distributed systems — UUID v4 and v7, Twitter Snowflake, ULID, database auto-increment limitations, multi-datacenter generation, clock skew, and base62 encoding.
A deep dive into URL shortener system design covering base62 encoding, hash collision handling, read-heavy optimization, database choice, Redis caching, analytics tracking, redirect flows, and scaling strategies.